Time of Flight (ToF) depth image processing methods are disclosed for resolving corruption of ToF depth images. In ToF depth imaging, the light can travel paths of different lengths before returning to the pixel. Thus, the light hitting the pixel can have travelled different distances, and the distance obtained from an estimation procedure assuming a single distance may be spurious. Systems and methods are disclosed for including a time-of-flight imager and processor which resolves the multiple paths, and outputs the multiple depths at each pixel.
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2. The image processing system of claim 1, wherein the processor is further configured to process the first set of measurements to determine a second set of measurements, wherein the second set of measurements is smaller than the first set of measurements.
3. The image processing system of claim 2, wherein the processor is further configured to perform dimensionality reduction on the first set of measurements to generate the second set of measurements.
4. The image processing system of claim 2, wherein the processor is further configured to perform discretization on the first set of measurements to generate the second set of measurements.
5. The image processing system of claim 4, wherein performing the discretization comprises selecting a discrete set of values from the first set of measurements, and wherein the look-up table comprises precomputed solutions for the discrete set of values.
6. The image processing system of claim 1, wherein the look-up table comprises first corrected depth data for a first subset of the first set of measurements and second corrected depth data for a second subset of the first set of measurements.
7. The image processing system of claim 1, wherein the processor is further configured to undergo a calibration step.
9. The method of claim 8, further comprising generating a second set of measurements using the first set of measurements, wherein the second set of measurements is smaller than the first set of measurements.
10. The method of claim 9, further comprising performing dimensionality reduction on the first set of measurements to generate the second set of measurements.
11. The method of claim 9, further comprising discretizing the first set of measurements to generate the second set of measurements.
12. The method of claim 11, wherein discretizing the first set of measurements comprises selecting a discrete set of values from the first set of measurements, and wherein the look-up table comprises stored precomputed solutions for the discrete set of values.
13. The method of claim 8, wherein the look-up table comprises first stored corrected depth data for a first subset of the first set of measurements and second stored corrected depth data for a second subset of the first set of measurements.
14. The method of claim 8, further comprising calibrating processor distance measurements.
16. The imaging apparatus of claim 15, further comprising means for processing the first set of measurements to determine a second set of measurements, wherein the second set of measurements is smaller than the first set of measurements.
17. The imaging apparatus of claim 16, wherein processing the first set of measurements to determine the second set of measurements includes performing dimensionality reduction on the first set of measurements to generate the second set of measurements.
18. The imaging apparatus of claim 16, wherein processing the first set of measurements to determine the second set of measurements includes performing discretization on the first set of measurements to generate the second set of measurements.
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December 6, 2019
April 23, 2024
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